code: def test_vqvae(self):
      model = JukeboxModel.from_pretrained(
          self.model_id, min_duration=0
      ).eval()
      set_seed(0)
      x = torch.rand((1, 5120, 1))
      with torch.no_grad():
          zs = model.vqvae.encode(
              x, start_level=2, bs_chunks=x.shape[0]
          )
      torch.testing.assert_allclose(
          zs[0][0], torch.tensor(self.EXPECTED_VQVAE_ENCODE)
      )
  
      with torch.no_grad():
          x = model.vqvae.decode(
              zs, start_level=2, bs_chunks=x.shape[0]
          )
      torch.testing.assert_allclose(
          x[0, :40, 0],
          torch.tensor(self.EXPECTED_VQVAE_DECODE),
          atol=1e-4,
          rtol=1e-4,
      )
  
file_path: transformers/tests/models/jukebox/test_modeling_jukebox.py
imports: import unittest
  from unittest import skip
  from transformers import is_torch_available
  from transformers.testing_utils import require_torch, require_torch_accelerator, require_torch_fp16, slow, torch_device
  from transformers.trainer_utils import set_seed
label_desc: Use image node_id 5 for calling the Jukebox1bModelTester obj's underlying member method code with example usage: obj.test_vqvae() without return types